AI Systems and Solutions Engineering Manager

Intel Intel · Semiconductors · California, Santa Clara, United States

Leads a team of engineers responsible for the design and development of integrated end-to-end hardware and/or software systems for AI products and autonomous systems, including deep learning hardware structures. Oversees the development of large-scale continuous delivery systems for AI product development and influences the AI product roadmap based on deep understanding of AI/DL algorithms and customer requirements. Drives strategy for AI research capabilities and manages teams to execute through clear goal setting and accountability.

What you'd actually do

  1. Own and drive the hardware product strategy and multigeneration portfolio roadmap for AI GPU platforms and system solutions.
  2. Build, lead, and mentor the Hardware Product Management team, setting expectations for technical rigor, decision quality, and execution discipline.
  3. Establish best practices for requirements definition, roadmap development, customer input synthesis, and cross functional alignment.
  4. Engage directly with strategic customers and partners to understand deployment environments, workload characteristics, and evolving requirements.
  5. Translate customer insights into clear, actionable product requirements and platform priorities.

Skills

Required

  • Hardware product strategy
  • Multigeneration portfolio roadmap
  • AI GPU platforms
  • System solutions
  • Team leadership
  • Mentoring
  • Technical rigor
  • Decision quality
  • Execution discipline
  • Requirements definition
  • Roadmap development
  • Customer input synthesis
  • Cross-functional alignment
  • Customer engagement
  • Workload analysis
  • Product requirements translation
  • Platform prioritization
  • Hardware roadmap representation
  • Stakeholder alignment (VP/SVP level)
  • Product tradeoff arbitration
  • GPU architecture
  • Semiconductor design
  • Manufacturing
  • Validation
  • System integration
  • Executive communication
  • Product management excellence
  • MS in Electrical Engineering, Computer Engineering, or related field
  • 12+ years of experience in semiconductor, systems, or platform level product development

Nice to have

  • PhD in Electrical Engineering, Computer Engineering, or related field
  • 10+ years of experience in semiconductor, systems, or platform level product development

What the JD emphasized

  • deep familiarity with GPU architecture and AI workloads
  • align architecture, silicon, systems, software, and go-to-market teams at scale
  • grounded in real customer usage, market constraints, and long term platform strategy
  • technical rigor
  • decision quality
  • execution discipline
  • requirements definition
  • roadmap development
  • customer input synthesis
  • cross functional alignment
  • strategic customers and partners
  • workload characteristics
  • evolving requirements
  • product requirements
  • platform priorities
  • hardware roadmap and strategy
  • senior product authority
  • senior leaders
  • shared priorities
  • delivery commitments
  • product level tradeoffs
  • performance, power, cost, yield, schedule, and manufacturability
  • hardware roadmap decisions
  • software enablement
  • platform readiness
  • cutting-edge technologies and methodologies
  • product design and development process
  • product authority
  • consistent product narrative
  • decision integrity
  • MS in Electrical Engineering, Computer Engineering, or related field, with 12+ years of experience in semiconductor, systems, or platform level product development
  • Demonstrated success leading hardware product management teams for complex silicon platforms or systems across multiple product cycles
  • Deep technical fluency in GPU architecture, semiconductor design, manufacturing, validation, and system integration, with the ability to arbitrate high impact tradeoffs
  • Proven ability to influence and align VP and SVP level stakeholders across engineering, architecture, systems, and got-o-market organizations
  • Strong track record of engaging strategic customers and partners to shape product direction and long term platform strategy
  • Exceptional executive communication skills, including the ability to synthesize complexity, frame decisions, and represent hardware product strategy in leadership forums
  • Demonstrated commitment to mentoring PM talent, building strong teams, and raising the overall bar for product management excellence

Other signals

  • AI GPU platforms
  • system solutions
  • deep learning hardware
  • autonomous systems
  • AI product roadmap